Came across this article about using AI in teaching by Lew Ludwig, a math professor. This paragraph stuck with me--I'm just going to quote it because I don't have time to discuss it:
Ethan Mollick put a name to this a few weeks ago in his post “The Overhang.” He argues that as AI gets better at producing things, what matters is what we bring to it, and he names four human advantages: deep knowledge, wide knowledge, taste, and agency. Deep knowledge is the expertise that lets a golf pro see the flaw in a swing at a glance. Wide knowledge is knowing enough about other fields to ask for what you want. Agency is the willingness to explore what the tool can do before someone tells you. And taste is the ability to look at what the AI hands you and know which parts to keep, which to discard, and which to use as raw material for something it would never have made on its own. Mollick's point is that taste used to be a luxury. Making things was slow and expensive, so the constraint was always producing enough stuff. Now making is fast and cheap. The scarce resource is knowing what to keep.
